Digital Sentiment, Risk Communication, and Climate Disaster Narratives: A Big Data Analysis of Social Platform Discourse in Sumatera, Indonesia

Abstract

The paper explores digital sentiment, risk communication, and narrations of major disasters in social media discourse around disaster events in Sumatra, Indonesia. In relation to climate risk quantification, understanding how people identify and respond to disasters via digital platforms is significant. A mixed-methods approach is employed in this study by intertwining big data analytics utilizing Drone Emprit Academic with qualitative discourse analysis. Social media evidence was gathered grounded in disaster-related algorithms within a definite time frame and dissected using sentiment analysis, topic modelling, and network investigation. The most obvious finding to emerge from the analysis is that negative sentiment dominates public discourse, initially as the disaster unfolds, exposing intense risk perception and hysterical responses such as fear and anxiety. Additionally, sentiment trajectory shifts toward more positive and neutral, attributing adaptive responses and the development of solidarity narrations. The research further determines dominant themes attributed to disaster impact, government feedback, and humanitarian concerns, including a networked communication design represented by diverse actors. This study contributes to the literature by assimilating sentiment analysis, risk communication, and narration context to present a higher holistic understanding of digital disaster communication in a developing country setting.